Secure Data Aggregation Based on End-to-End Homomorphic Encryption in IoT-Based Wireless Sensor Networks

Kumar, Mukesh; Sethi, Monika; Rani, Shalli; Sah, Dipak Kumar; AlQahtani, Salman A.; Al-Rakhami, Mabrook

doi:10.3390/s23136181

Cited by 10 publications

(2 citation statements)

References 27 publications

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“…While emphasizing data security, their approach does not delve into the distributed processing of encrypted data across the network. Mukesh Kumar et al presented an End-to-End Homomorphic Encryption (EEHE) system for IoT-based WSNs, concentrating on secure data aggregation and the application of aggregator functions on encrypted messages [14]. This study shares a conceptual similarity with our proposed methodology regarding using HE for secure data aggregation.…”

Section: IImentioning

confidence: 93%

Advancing Wireless Sensor Network Security through the Implementation of Homomorphic Encryption for Secure and Private Image Processing

Idris,

issahku

2024

IJRASET

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Data security and privacy in image processing are of utmost concern. This paper presents an innovative architecture for integrating Homomorphic Encryption (HE) in Wireless Sensor Networks (WSNs), focusing on enhancing data security and privacy in image processing. Central to this architecture are sensor nodes equipped with Paillier Homomorphic Encryption capabilities, ensuring data confidentiality from the collection point. The network features intermediate aggregator nodes that perform homomorphic computations, such as summing or averaging, on encrypted data, maintaining its confidentiality. The central server, equipped with the private key, decrypts the aggregated data and is pivotal for complex data analyses, ensuring secrecy until the final stage. This architecture, characterized by the implementation of Homomorphic Encryption, allows for secure data encryption at the sensor nodes and its subsequent processing in an encrypted form. The design is bolstered by a robust mathematical framework, enhancing the system's security and effectiveness. This approach secures data within WSNs and harnesses the advanced capabilities of Homomorphic Encryption for data privacy and safety throughout the network's lifecycle

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Section: IImentioning

confidence: 93%

Advancing Wireless Sensor Network Security through the Implementation of Homomorphic Encryption for Secure and Private Image Processing

Idris,

issahku

2024

IJRASET

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“…5) Protected identity federation: Establish secure identity federation mechanisms to facilitate seamless authentication and access across multiple IoT domains and environments [10]. Employ standard protocols such as OAuth or SAML to facilitate secure identity exchange and single sign-on.…”

Section: Security and Privacy Framework For Iot Device Identity Manag...mentioning

confidence: 99%

Enhancing IoT Security and Privacy with Claims-based Identity Management

Bhargavi,

Pachipala

2023

IJACSA

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The Internet of Things (IoT) has ushered in a new era of ubiquitous connectivity among devices, necessitating robust identity management (IdM) solutions to address privacy, security, and efficiency challenges. In this study, it delve into various IdM approaches in the context of IoT, examining their implications for privacy preservation, user experience, integration, and efficiency. In this paper a methodology is an innovative holistic IdM system that leverages emerging cryptographic technologies and a claims-based approach. This system empowers both users and smart objects to manage data disclosure via partial identities and efficient proof mechanisms, ensuring privacy while facilitating seamless interactions which integrate the proposed IdM system with Distributed Capability-Based Access Control (DCapBAC) and Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to cater to diverse IoT scenarios. Through a comparative evaluation, it is highlighted that the limitations of conventional IdM methods and OAuthbased approaches, underscored by the superior efficiency exhibited by our proposed system. Notably efficient, the IdM system stands as a paramount solution for ensuring secure, private, and resource-effective interactions within the everexpanding IoT landscape. As the IoT domain continues to evolve, embracing advanced identity management systems like our proposal becomes indispensable for fostering trust, bolstering security, and optimizing interactions across interconnected devices and services.

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Hybrid optimization‐based topology construction and DRNN‐based prediction method for data reduction in IoT

Pawar,

Jadhav

2024

Int J Communication

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SummaryThe Internet of Things (IoT) acts as a prevalent networking setup that plays a vital role in everyday activities due to the increased services provided through uniform data collection. In this research paper, a hybrid optimization approach for the construction of heterogeneous multi‐hop IoT wireless sensor network (WSN) network topology and data aggregation and reduction is performed using a deep learning model. Initially, the IoT network is stimulated and the network topology is constructed using Namib Beetle Spotted Hyena Optimization (NBSHO) by considering different network parameters and encoding solutions. Moreover, the data aggregation and reduction in the IoT network are performed using a Deep Recurrent Neural Network (DRNN)‐based prediction model. In addition, the performance improvement of the designed NBSHO + DRNN approach is validated. Here, the designed NBSHO + DRNN method achieved a packet delivery ratio (PDR) of 0.469, energy of 0.367 J, prediction error of 0.237, and delay of 0.595 s.

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Secure Data Aggregation Based on End-to-End Homomorphic Encryption in IoT-Based Wireless Sensor Networks

Cited by 10 publications

References 27 publications

Advancing Wireless Sensor Network Security through the Implementation of Homomorphic Encryption for Secure and Private Image Processing

Advancing Wireless Sensor Network Security through the Implementation of Homomorphic Encryption for Secure and Private Image Processing

Enhancing IoT Security and Privacy with Claims-based Identity Management

Hybrid optimization‐based topology construction and DRNN‐based prediction method for data reduction in IoT

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